Contact Center Forward Deployed Engineer, AI

IBM

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: ParamusCharlotteRaleighBostonAtlantaDallasHoustonAustinCambridgeChicagoDetroitNew York
Posted: 3 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Similar $201k

$155k $247k

below market most similar roles pay here above market

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IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

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Listed pay typically runs $180,812–$215,000 across 9 roles with salary data.

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At a glance

TL;DR · Contact Center Forward Deployed Engineer, AI

Role Posting Log in to save

As a Contact Center Forward Deployed Engineer – AI within IBM Consulting, you will work directly with clients to transform complex business challenges into production-ready AI solutions. You will partner with business and technical teams to identify use cases, develop end-to-end GenAI, RAG, and agentic AI applications, and integrate these solutions with enterprise systems and APIs. Your daily work involves designing LLM-powered agents, prompt engineering, and establishing evaluation frameworks. You will utilize a technical stack including Python, SQL, LangChain, LangGraph, CrewAI, and PyTorch, while deploying on platforms like AWS Bedrock, Azure AI Foundry, or Google Vertex AI. You must also apply MLOps/LLMOps practices, including monitoring and responsible AI guardrails, to ensure that all deployed solutions are secure, reliable, and scalable.

Skills

Python SQL GenAI RAG LangChain LangGraph CrewAI AutoGen MLOps LLMOps PyTorch scikit-learn Pandas Spark AWS Bedrock Azure AI Foundry Google Vertex AI Milvus Elasticsearch pgvector Pinecone Docker Kubernetes Git FastAPI Streamlit React

What you'll do

Identify business opportunities and define AI use cases with client technical and business teams.
Develop end-to-end GenAI, RAG, and agentic AI applications using LangGraph, CrewAI, and cloud platforms.
Design LLM-powered agents featuring tool use, orchestration, prompt engineering, and evaluation frameworks.
Prepare structured and unstructured data and integrate AI solutions with enterprise systems and APIs.
Apply MLOps/LLMOps practices to ensure AI solutions are secure, reliable, and production-ready.
Present insights and demonstrate outcomes to support client adoption of new AI solutions.
Convert successful AI solutions into reusable assets for future client engagements.

What we're looking for

Bachelor's Degree in Computer Science, Engineering, Data Science, or a related field.
Master's or PhD in a technical or quantitative field (preferred).
5-7+ years of experience in AI/ML, data science, or software engineering delivering production AI solutions.
Strong Python and SQL skills with experience building GenAI and agentic AI applications using LangChain, LangGraph, or CrewAI.
Experience building GenAI applications with LLMs, RAG, prompt engineering, embeddings, vector databases, and LLM evaluation.
Experience designing agentic AI workflows using frameworks like LangChain, LangGraph, CrewAI, or AutoGen.
Experience with machine learning and data processing using scikit-learn, PyTorch, Pandas, or Spark.
Experience integrating AI solutions using APIs, cloud platforms (AWS Bedrock, Azure AI, or Google Vertex AI), and tools like Git, Docker, or Kubernetes.
Experience with LLM fine-tuning, AI evaluation and governance (preferred).
Industry experience in high tech, electronics, or manufacturing (preferred).
Background in forward deployed engineering, solutions engineering, or client-facing consulting (preferred).
Front-end development experience, cloud/AI certifications, or open-source AI contributions (preferred).
Strong client-facing skills to translate business challenges into technical solutions for diverse audiences.

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